Chakradhara Panda, Vijay Kumar Garlapti, P. Konar, P. Chattopadhyay
This paper presents the development of a wavelet-based algorithm, for distinguishing between magnetizing inrush and internal faults of the power transformer. The proposed technique consists of a preprocessing unit based on Continuous wavelet transform (CWT) in combination with an artificial neural network (ANN) for detecting and classifying faults. The CWT acts as an extractor of distinctive features in the transient current signals at the relay location. This information is then fed into an ANN for classifying fault, normal and magnetizing inrush conditions. The results presented clearly showed that the proposed technique is very fast, computationally efficient and intelligent enough to accurately discriminate between magnetizing inrush, normal and faults in the transformer
{"title":"A Hybrid Wavelet--ANN Approach in Transformer Protection","authors":"Chakradhara Panda, Vijay Kumar Garlapti, P. Konar, P. Chattopadhyay","doi":"10.1109/ARTCOM.2010.70","DOIUrl":"https://doi.org/10.1109/ARTCOM.2010.70","url":null,"abstract":"This paper presents the development of a wavelet-based algorithm, for distinguishing between magnetizing inrush and internal faults of the power transformer. The proposed technique consists of a preprocessing unit based on Continuous wavelet transform (CWT) in combination with an artificial neural network (ANN) for detecting and classifying faults. The CWT acts as an extractor of distinctive features in the transient current signals at the relay location. This information is then fed into an ANN for classifying fault, normal and magnetizing inrush conditions. The results presented clearly showed that the proposed technique is very fast, computationally efficient and intelligent enough to accurately discriminate between magnetizing inrush, normal and faults in the transformer","PeriodicalId":398854,"journal":{"name":"2010 International Conference on Advances in Recent Technologies in Communication and Computing","volume":"1032 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-10-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"120876385","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Process variation has become a major concern in the design of many nanometer circuits, including interconnect pipelines. This paper provides a comprehensive overview of the types and sources of all aspects of process variations in driver –interconnect-load system. The primary sources of manufacturing variation include Deposition, Chemical Mechanical Planarization (CMP), Etching, Resolution Enhancement Technology (RET). Process variations manifest themselves as the uncertainties of circuit performance, such as delay, noise and power consumption. The impacts of these process variations on circuit delay are discussed in this paper for three different technologies i.e 130nm, 70nm and 45nm. The comparison of results between these three technologies shows that as device size shrinks the process variation becomes a dominant factor and subsequently increases the uncertainty of the delays.
{"title":"Propagation Delay Variations under Process Deviation in Driver Interconnect Load System","authors":"K. G. Verma, B. Kaushik, R. Singh","doi":"10.1109/ARTCOM.2010.105","DOIUrl":"https://doi.org/10.1109/ARTCOM.2010.105","url":null,"abstract":"Process variation has become a major concern in the design of many nanometer circuits, including interconnect pipelines. This paper provides a comprehensive overview of the types and sources of all aspects of process variations in driver –interconnect-load system. The primary sources of manufacturing variation include Deposition, Chemical Mechanical Planarization (CMP), Etching, Resolution Enhancement Technology (RET). Process variations manifest themselves as the uncertainties of circuit performance, such as delay, noise and power consumption. The impacts of these process variations on circuit delay are discussed in this paper for three different technologies i.e 130nm, 70nm and 45nm. The comparison of results between these three technologies shows that as device size shrinks the process variation becomes a dominant factor and subsequently increases the uncertainty of the delays.","PeriodicalId":398854,"journal":{"name":"2010 International Conference on Advances in Recent Technologies in Communication and Computing","volume":"133 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-10-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132480534","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Diagnosis of Parkinson’s disease (PD) is a challenging problem for medical community. Typically characterized by tremor, PD occurs due to the loss of dopamine in the brain’s thalamic region that results in involuntary or oscillatory movement in the body. The early stage of the PD is referred as resting tremors, which appears when the muscles are relaxed. It is well known that surface EMG recording provides clinical information on the neuro-physiological characteristics of the tremors. This paper discusses the detection of resting tremors by extracting power spectral density (PSD) features from EMGs. Two methods namely, PSD by Welch and Burgs are applied by configuring the order of the predictors and are then classified using a recurrent neural network model, Elman Neural Network (REN). Experiments are performed using EMG patterns and statistical measures such as mean and maximum of PSD are used to classify the normal and abnormal PD subjects. It is found from the experimental results that the mean value of power spectral density by Burg with recurrent neural network classifier yields a classification accuracy of 95.6%. The proposed work need to be validated with larger datasets for real -time clinical application.
{"title":"Automated Detection of PD Resting Tremor Using PSD with Recurrent Neural Network Classifier","authors":"R. Arvind, B. Karthik, N. Sriraam, J. Kannan","doi":"10.1109/ARTCOM.2010.33","DOIUrl":"https://doi.org/10.1109/ARTCOM.2010.33","url":null,"abstract":"Diagnosis of Parkinson’s disease (PD) is a challenging problem for medical community. Typically characterized by tremor, PD occurs due to the loss of dopamine in the brain’s thalamic region that results in involuntary or oscillatory movement in the body. The early stage of the PD is referred as resting tremors, which appears when the muscles are relaxed. It is well known that surface EMG recording provides clinical information on the neuro-physiological characteristics of the tremors. This paper discusses the detection of resting tremors by extracting power spectral density (PSD) features from EMGs. Two methods namely, PSD by Welch and Burgs are applied by configuring the order of the predictors and are then classified using a recurrent neural network model, Elman Neural Network (REN). Experiments are performed using EMG patterns and statistical measures such as mean and maximum of PSD are used to classify the normal and abnormal PD subjects. It is found from the experimental results that the mean value of power spectral density by Burg with recurrent neural network classifier yields a classification accuracy of 95.6%. The proposed work need to be validated with larger datasets for real -time clinical application.","PeriodicalId":398854,"journal":{"name":"2010 International Conference on Advances in Recent Technologies in Communication and Computing","volume":"47 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-10-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133181532","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Sudip Dogra, S. Chatterjee, Ritwik Ray, Saustav Ghosh, Debharshi Bhattacharya, S. Sarkar
White meat basically comprises of poultry products. Due to its health hazard many people are shunning away from red meat. The primary source of white meat is poultry farming where the practice of raising fowls, such as chickens, turkeys, ducks etc is carried out.. The entire requirement of white meat and eggs mostly come from these poultry products. The primary threat to poultry farming is avian influenza. This disease being highly contagious causes a huge loss both in terms of money and business property. Furthermore, human beings suffer a high chance of being infected by this disease. In this paper we have presented a novel scheme for recognition of bird flu using RFID at a very early stage so that its spread can be controlled quickly.
{"title":"A Novel Proposal for Detection of Avian Influenza and Managing Poultry in a Cost Efficient Way Implementing RFID","authors":"Sudip Dogra, S. Chatterjee, Ritwik Ray, Saustav Ghosh, Debharshi Bhattacharya, S. Sarkar","doi":"10.1109/ARTCOM.2010.48","DOIUrl":"https://doi.org/10.1109/ARTCOM.2010.48","url":null,"abstract":"White meat basically comprises of poultry products. Due to its health hazard many people are shunning away from red meat. The primary source of white meat is poultry farming where the practice of raising fowls, such as chickens, turkeys, ducks etc is carried out.. The entire requirement of white meat and eggs mostly come from these poultry products. The primary threat to poultry farming is avian influenza. This disease being highly contagious causes a huge loss both in terms of money and business property. Furthermore, human beings suffer a high chance of being infected by this disease. In this paper we have presented a novel scheme for recognition of bird flu using RFID at a very early stage so that its spread can be controlled quickly.","PeriodicalId":398854,"journal":{"name":"2010 International Conference on Advances in Recent Technologies in Communication and Computing","volume":"199 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-10-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122561495","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The advancement in IC technology has led the recent trend of designing hybrid systems to benefit both analog and the digital world. Among analog building blocks, Multifunctional filters & Multiphase oscillator constitutes an important building block. We propose a novel current mode digitally programmable multifunctional filter and deduce a programmable multiphase oscillator providing four quadrature phase outputs. For the introduction of digital control in analog systems we use a digital control module comprising of R/2R ladder and analog switch array. The parameters of analog systems results in the form of digital word (N) of n-bits. All the realizations are designed and verified using PSPICE simulation tool with good results in support of the theory
{"title":"Digitally Programmable Multifunctional Filter and Multiphase Oscillator Using MOCCCII","authors":"A. Imran, M. Siddiqi","doi":"10.1109/ARTCOM.2010.84","DOIUrl":"https://doi.org/10.1109/ARTCOM.2010.84","url":null,"abstract":"The advancement in IC technology has led the recent trend of designing hybrid systems to benefit both analog and the digital world. Among analog building blocks, Multifunctional filters & Multiphase oscillator constitutes an important building block. We propose a novel current mode digitally programmable multifunctional filter and deduce a programmable multiphase oscillator providing four quadrature phase outputs. For the introduction of digital control in analog systems we use a digital control module comprising of R/2R ladder and analog switch array. The parameters of analog systems results in the form of digital word (N) of n-bits. All the realizations are designed and verified using PSPICE simulation tool with good results in support of the theory","PeriodicalId":398854,"journal":{"name":"2010 International Conference on Advances in Recent Technologies in Communication and Computing","volume":"51 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-10-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124940308","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The goal of this application is to implement a hybrid ad-hoc routing protocol, using the 802.11 wireless protocols. Our implementation enables communication between several wireless stations, on a dynamic network without using any infrastructure, i.e. using peer-to-peer mode, rather than Access Points. Two distant units can communicate even when there is no direct connection between them. We have implemented the Direct Sequence Distance Vector (DSDV) algorithm, which is a pro-active table driven algorithm in Wireless Network. The routing in each station is executed according to local routing table. The tables are continually maintained and updated. We developed the application in Java, which has inherent support for network operations. Thus, it is platform independent, and can run with various OS and wireless cards. In order to demonstrate the operation of the algorithm we wrote a Unicode Short Message Text (USMT) application that uses the routing protocol services as a sub-layer. The USMT application enables sending of text messages from any unit to any other unit in the network. It also graphically presents the local routing tables information.
{"title":"Implementation of Hybrid Ad-Hoc Routing Protocol","authors":"S. S. Kumar, M. N. Kumar, S. V.S.","doi":"10.1109/ARTCOM.2010.14","DOIUrl":"https://doi.org/10.1109/ARTCOM.2010.14","url":null,"abstract":"The goal of this application is to implement a hybrid ad-hoc routing protocol, using the 802.11 wireless protocols. Our implementation enables communication between several wireless stations, on a dynamic network without using any infrastructure, i.e. using peer-to-peer mode, rather than Access Points. Two distant units can communicate even when there is no direct connection between them. We have implemented the Direct Sequence Distance Vector (DSDV) algorithm, which is a pro-active table driven algorithm in Wireless Network. The routing in each station is executed according to local routing table. The tables are continually maintained and updated. We developed the application in Java, which has inherent support for network operations. Thus, it is platform independent, and can run with various OS and wireless cards. In order to demonstrate the operation of the algorithm we wrote a Unicode Short Message Text (USMT) application that uses the routing protocol services as a sub-layer. The USMT application enables sending of text messages from any unit to any other unit in the network. It also graphically presents the local routing tables information.","PeriodicalId":398854,"journal":{"name":"2010 International Conference on Advances in Recent Technologies in Communication and Computing","volume":"392 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-10-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124653873","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Ch. V. M. K. Hari, Prasad Reddy P.V.G.D., M. Jagadeesh, G. Ganesh
One of the biggest challenges in Software Engineering is accurately forecasting how much time and effort it will take either to develop a system. So far no model has proved to be successful at effectively and consistently predicting software development cost due to the lot of uncertainty factor of input size. In this paper we proposed an Interval Type 2 Fuzzy logic for software cost estimation. The inputs are fuzzified by using Takagi-Sugeno fuzzy controller of Universe Discourse with mean and standard deviation of size values affects the control performance. The software size can be regarded as a fuzzy set yielding the cost estimate also inform of a fuzzy set. The uncertainty is an inherit part in cost estimation. We reduce the uncertainty produced by the Type-1 functions by using Type-2 Fuzzy logic. We considered means FOU`s as a firing strength. The model deals effectively with imprecise and uncertain input and enhances the reliability of software cost estimation. The estimated effort is optimized using the developed model and tested on NASA software projects on the basis of three criterions for assessment of software cost estimation models. Comparison of the all models is done and it is found that the developed model provide better estimation.
{"title":"Interval Type-2 Fuzzy Logic for Software Cost Estimation Using TSFC with Mean and Standard Deviation","authors":"Ch. V. M. K. Hari, Prasad Reddy P.V.G.D., M. Jagadeesh, G. Ganesh","doi":"10.1109/ARTCOM.2010.40","DOIUrl":"https://doi.org/10.1109/ARTCOM.2010.40","url":null,"abstract":"One of the biggest challenges in Software Engineering is accurately forecasting how much time and effort it will take either to develop a system. So far no model has proved to be successful at effectively and consistently predicting software development cost due to the lot of uncertainty factor of input size. In this paper we proposed an Interval Type 2 Fuzzy logic for software cost estimation. The inputs are fuzzified by using Takagi-Sugeno fuzzy controller of Universe Discourse with mean and standard deviation of size values affects the control performance. The software size can be regarded as a fuzzy set yielding the cost estimate also inform of a fuzzy set. The uncertainty is an inherit part in cost estimation. We reduce the uncertainty produced by the Type-1 functions by using Type-2 Fuzzy logic. We considered means FOU`s as a firing strength. The model deals effectively with imprecise and uncertain input and enhances the reliability of software cost estimation. The estimated effort is optimized using the developed model and tested on NASA software projects on the basis of three criterions for assessment of software cost estimation models. Comparison of the all models is done and it is found that the developed model provide better estimation.","PeriodicalId":398854,"journal":{"name":"2010 International Conference on Advances in Recent Technologies in Communication and Computing","volume":"183 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-10-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125830363","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
In this work an adaptive tracking control strategy for a class of non affine delayed systems subjected to actuator saturation is proposed. Self recurrent wavelet neural network (SRWNN) is used to approximate the uncertainties present in the system as well as to identify and compensate the nonlinearities introduced in the system due to actuator saturation. By using suitable transformation the system under consideration is first converted into an affine like form and subsequently an adaptive backstepping control strategy is developed to assure the stable tracking of nonlinear non affine system. In addition robust control terms are also designed to attenuate the approximation error due to SRWNN. Adaptation laws are developed for the online tuning of the wavelet parameters and the stability of the overall system is assured by using the Lyapunov-Krasovskii functional. The effectiveness of theoretical development is verified by a numerical example.
{"title":"Adaptive Tracking Control for a Class of Uncertain Non-affine Delayed Systems Subjected to Input Constraints Using Self Recurrent Wavelet Neural Network","authors":"M. Sharma, Medicaps Instt","doi":"10.1109/ARTCOM.2010.47","DOIUrl":"https://doi.org/10.1109/ARTCOM.2010.47","url":null,"abstract":"In this work an adaptive tracking control strategy for a class of non affine delayed systems subjected to actuator saturation is proposed. Self recurrent wavelet neural network (SRWNN) is used to approximate the uncertainties present in the system as well as to identify and compensate the nonlinearities introduced in the system due to actuator saturation. By using suitable transformation the system under consideration is first converted into an affine like form and subsequently an adaptive backstepping control strategy is developed to assure the stable tracking of nonlinear non affine system. In addition robust control terms are also designed to attenuate the approximation error due to SRWNN. Adaptation laws are developed for the online tuning of the wavelet parameters and the stability of the overall system is assured by using the Lyapunov-Krasovskii functional. The effectiveness of theoretical development is verified by a numerical example.","PeriodicalId":398854,"journal":{"name":"2010 International Conference on Advances in Recent Technologies in Communication and Computing","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-10-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129097970","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
B. Nair, M. Minuvarthini, Sujithra B., V. Mohandas
Stock market prediction is an important area of financial forecasting, which is of great interest to stock investors, stock traders and applied researchers. Main issues in developing a fully automated stock market prediction system are: feature extraction from the stock market data, feature selection for highest prediction accuracy, the dimensionality reduction of the selected feature set and the accuracy and robustness of the prediction system. In this paper, an automated decision tree-adaptive neuro-fuzzy hybrid automated stock market prediction system is proposed. The proposed system uses technical analysis (traditionally used by stock traders) for feature extraction and decision tree for feature selection. Dimensionality reduction is carried out using fifteen different dimensionality reduction techniques. The dimensionality reduction technique producing the best prediction accuracy is selected to produce the reduced dataset. The reduced dataset is then applied to the adaptive neuro-fuzzy system for the next-day stock market prediction. The neuro-fuzzy system forms the stock market model adaptively, based on the features present in the reduced dataset. The proposed system is tested on the Bombay Stock Exchange sensitive index (BSE-SENSEX). The results show that the proposed hybrid system produces much higher accuracy when compared to stand-alone decision tree based system and ANFIS based system without feature selection and dimensionality reduction.
{"title":"Stock Market Prediction Using a Hybrid Neuro-fuzzy System","authors":"B. Nair, M. Minuvarthini, Sujithra B., V. Mohandas","doi":"10.1109/ARTCOM.2010.76","DOIUrl":"https://doi.org/10.1109/ARTCOM.2010.76","url":null,"abstract":"Stock market prediction is an important area of financial forecasting, which is of great interest to stock investors, stock traders and applied researchers. Main issues in developing a fully automated stock market prediction system are: feature extraction from the stock market data, feature selection for highest prediction accuracy, the dimensionality reduction of the selected feature set and the accuracy and robustness of the prediction system. In this paper, an automated decision tree-adaptive neuro-fuzzy hybrid automated stock market prediction system is proposed. The proposed system uses technical analysis (traditionally used by stock traders) for feature extraction and decision tree for feature selection. Dimensionality reduction is carried out using fifteen different dimensionality reduction techniques. The dimensionality reduction technique producing the best prediction accuracy is selected to produce the reduced dataset. The reduced dataset is then applied to the adaptive neuro-fuzzy system for the next-day stock market prediction. The neuro-fuzzy system forms the stock market model adaptively, based on the features present in the reduced dataset. The proposed system is tested on the Bombay Stock Exchange sensitive index (BSE-SENSEX). The results show that the proposed hybrid system produces much higher accuracy when compared to stand-alone decision tree based system and ANFIS based system without feature selection and dimensionality reduction.","PeriodicalId":398854,"journal":{"name":"2010 International Conference on Advances in Recent Technologies in Communication and Computing","volume":"33 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-10-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114479072","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This paper presents the design of a wide bandwidth high performance CMOS realization of dual-output second generation current conveyor (CCII±) at 32nm technology node. HSPICE simulation shows that voltage and current bandwidths in excess of 10GHz are obtained, thus making the module quite suitable for applications in the microwave range of frequencies. Besides, the circuit is able to operate at reduced power supply of ±0.9V and presents 2.54k??? as Rx input port resistance for a control current of 8uA.
{"title":"Design of High Frequency Low Power CMOS Dual-Output Current Conveyor at 32nm Technology Node","authors":"A. Imran, M. Hasan, M. W. Akram","doi":"10.1109/ARTCOM.2010.85","DOIUrl":"https://doi.org/10.1109/ARTCOM.2010.85","url":null,"abstract":"This paper presents the design of a wide bandwidth high performance CMOS realization of dual-output second generation current conveyor (CCII±) at 32nm technology node. HSPICE simulation shows that voltage and current bandwidths in excess of 10GHz are obtained, thus making the module quite suitable for applications in the microwave range of frequencies. Besides, the circuit is able to operate at reduced power supply of ±0.9V and presents 2.54k??? as Rx input port resistance for a control current of 8uA.","PeriodicalId":398854,"journal":{"name":"2010 International Conference on Advances in Recent Technologies in Communication and Computing","volume":"51 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-10-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134341015","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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